Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Onevium/awesome-claude-skills --skill discovery-questionsgit clone --depth 1 https://github.com/Onevium/awesome-claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/onevium/awesome-claude-skills/discovery-questions)<a href="https://agentmods.dev/skills/onevium/awesome-claude-skills/discovery-questions"><img src="https://agentmods.dev/badge/skills/onevium/awesome-claude-skills/discovery-questions/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/onevium/awesome-claude-skills/discovery-questions"><img src="https://agentmods.dev/badge/skills/onevium/awesome-claude-skills/discovery-questions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00084 | $0.00793 |
| Opus 5 | $0.00042 | $0.00396 |
| Sonnet 5 | $0.00017 | $0.00159 |
| Haiku 4.5 | $0.00008 | $0.00079 |
Grade A, and why
discovery-questions scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
设计启动问题
在高保真工作前一次性补齐真正影响方向的信息。问题的价值来自答案会改变设计，而不是因为提问显得谨慎。
1. 先读取已有材料
完整查看用户已提供的代码、截图、品牌规范、设计系统、UI Kit、需求和参考链接。能从材料确认的内容不要重复询问。
2. 判断是否需要提问
以下信息缺失且会改变结果时才问：
- 目标用户、业务目标或主要行动。
- 输出媒介、范围、保真度或目标设备。
- 必须遵循的品牌、设计系统、现有产品或参考。
- 需要多少方向，以及主要探索视觉、布局、交互、流程还是文案。
- 创新程度、明确禁区和必须保留内容。
- 最终哪些变量需要允许用户现场调整。
若只是标签、默认值或两个等价实现，直接做出合理决定并在交付时说明。精确复刻、小修复和上下文充分的后续任务应跳过提问。
3. 组成一次性问题集
根据歧义程度提出通常 3–6 个、最多约 10 个问题。优先级从高到低排列，避免为了凑数提问。
按任务补充：
- 演示文稿：受众知识水平、时长或页数、语气、来源材料、是否需要讲者备注。
- 落地页：主要行动、核心人群、喜欢与拒绝的参考、移动端或桌面端优先。
- 原型：完整流程、屏幕列表、保真度、设备框架、目标状态和示例数据。
- 品牌方向：三个形容词、行业语境、参考设计中具体喜欢的部分和禁用风格。
4. 提问并停下
一次性给出编号问题；运行环境提供结构化提问工具时可以使用。选择题应提供“帮我决定”和开放填写入口，但不要硬塞不适用的选项。
发出问题后结束当前轮次，等待用户回答。不要提前猜答案继续制作。
5. 收到答案后执行
简要复述最影响方向的选择，指出明显矛盾，再进入合适的制作流程。后续遇到小决定时自主判断；只有新信息会实质改变方向时才再次提问。
示例
输入：“给我们的新 API 产品做一个落地页。”
**输出：**一次性询问现有品牌或网站、主要行动、核心人群、需要探索的方向数量与轴、目标设备和禁用风格，然后停止并等待答案。
来源与许可
本 Skill 基于 Trystan Sarrade 的 claude-design-system-prompt 进行中文化与 Claude Skill 规范适配。上游与本改编均按 MIT License 发布，详见 LICENSE.txt。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 61 lines · 84 tokens per session scan A adb160b408ab
discovery-questions is a skill published in the GitHub repository Onevium/awesome-claude-skills (1 stars, last pushed 14d ago), licensed MIT. It adds 84 tokens to every session and 793 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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